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Population PK/PD modelling of a new MAO-B inhibitor in young and elderly healthy volunteers.

J.B. Fau * & C. Dubruc *, F. Mentré **.

* : Sanofi-Synthelabo Research, Clinical Metabolism & Pharmacokinetics, Chilly-Mazarin, France.

The aim of this work was to investigate the population PK/PD relationship of SSR, a new MAO-B inhibitor, in healthy volunteers using NONMEM V. Data from 5 phase I studies were used with a total of 3964 PK and 3699 PD observations in 84 subjects (66 young from 18 to 40 years and 18 elderly from 65 to 85 years) after single or repeated administrations at six different doses.

The PK model, based on previous individual analyses, was a two-compartment model with zero order absorption including a lag time (ADVAN3, TRANS4). A multiplicative model for the random effects was used for all parameters (CL, V1, Q and V2) but inter-individual variability had to be fixed to zero for ALAG and D1. The error variance model was additive and multiplicative. Possible covariates (chemical batch, study number, gender, age, weight, creatinine clearance) were evaluated using graphical analysis, scientific plausibility, statistical significance and OF decrease. Only three covariates (chemical batch, weight and age group) were successfully included in the final PK model, using the FOCE interaction method.

After definition of the PK model, PD data (platelet MAO-B activity inhibition expressed as pmol/min/109) were studied. Again based on individual analyses, an inhibitory Emax sigmoid direct pharmacodynamic model was assumed (E = E0 – [ (E0-Emax) * Cpg / (EC50g + Cpg) ] ). Multiplicative random effects were used on all PD parameters (Emax, E0 and EC50) but had to be fixed to zero for g. The error variance model was purely multiplicative. Two methods of estimation were implemented : sequential (PK parameters, intra and inter-individual variabilities fixed to the values estimated in the PK analysis) and simultaneous population PK/PD fitting. The estimated parameters were similar and age group was identified as a significant PD covariate with both methods. The best PK/PD run was obtained after simultaneous PK and PD estimation with a slightly lower OF (12 points) when compared to sequential. However, the computation time was very large (approximately 12 hr vs 8 hr for the sequential method).

For this rich data analysis, sequential and simultaneous PK/PD modelling provided similar results in terms of typical parameter values, variabilities and identification of significant covariates. The results will be used to evaluate sampling protocols for population analysis of phase IIb/III studies in patients.